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Record W2995006437 · doi:10.1186/s13071-019-3848-2

Genetic and antigenic variation of the bovine tick-borne pathogen Theileria parva in the Great Lakes region of Central Africa

2019· article· en· W2995006437 on OpenAlexfundno aff
Gaston Amzati, Appolinaire Djikeng, David Odongo, H. Nimpaye, Kgomotso P. Sibeko-Matjila, Jean-Berckmans B. Muhigwa, Maxime Madder, Nathalie Kirschvink, Tanguy Marcotty

Bibliographic record

VenueParasites & Vectors · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
FundersUniversité de NamurAgence Universitaire de la FrancophonieBiotechnology and Biological Sciences Research CouncilInternational Livestock Research InstituteInternational Foundation for Science
KeywordsTheileria parvaEast Coast feverBiologyTickGenetic variationGenetic diversityAntigenic variationEntomologyGenotypeVirologyGeneticsZoologyGenePopulationParasite hosting

Abstract

fetched live from OpenAlex

BACKGROUND: Theileria parva causes East Coast fever (ECF), one of the most economically important tick-borne diseases of cattle in sub-Saharan Africa. A live immunisation approach using the infection and treatment method (ITM) provides a strong long-term strain-restricted immunity. However, it typically induces a tick-transmissible carrier state in cattle and may lead to spread of antigenically distinct parasites. Thus, understanding the genetic composition of T. parva is needed prior to the use of the ITM vaccine in new areas. This study examined the sequence diversity and the evolutionary and biogeographical dynamics of T. parva within the African Great Lakes region to better understand the epidemiology of ECF and to assure vaccine safety. Genetic analyses were performed using sequences of two antigen-coding genes, Tp1 and Tp2, generated among 119 T. parva samples collected from cattle in four agro-ecological zones of DRC and Burundi. RESULTS: The results provided evidence of nucleotide and amino acid polymorphisms in both antigens, resulting in 11 and 10 distinct nucleotide alleles, that predicted 6 and 9 protein variants in Tp1 and Tp2, respectively. Theileria parva samples showed high variation within populations and a moderate biogeographical sub-structuring due to the widespread major genotypes. The diversity was greater in samples from lowlands and midlands areas compared to those from highlands and other African countries. The evolutionary dynamics modelling revealed a signal of selective evolution which was not preferentially detected within the epitope-coding regions, suggesting that the observed polymorphism could be more related to gene flow rather than recent host immune-based selection. Most alleles isolated in the Great Lakes region were closely related to the components of the trivalent Muguga vaccine. CONCLUSIONS: Our findings suggest that the extensive sequence diversity of T. parva and its biogeographical distribution mainly depend on host migration and agro-ecological conditions driving tick population dynamics. Such patterns are likely to contribute to the epidemic and unstable endemic situations of ECF in the region. However, the fact that ubiquitous alleles are genetically similar to the components of the Muguga vaccine together with the limited geographical clustering may justify testing the existing trivalent vaccine for cross-immunity in the region.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.211
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2019
Admission routes1
Has abstractyes

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